Senior Fullstack Engineer - Product Platform Engineering

Pivotal Health; United States; On-site; USD 120,000 - 190,000; Full time

Job summary

Pivotal Health in the United States is seeking a senior platform engineer to own and evolve the core platform services used by product teams. You will design, build, and operate scalable cloud-native components with clear ownership over reliability and data interfaces.

The role focuses on extensible architectures, dependable data flows, and collaboration with product teams to deliver robust, scalable solutions across the reimbursement platform.

Qualifications

• 5+ years of experience in fullstack, backend or platform software engineering.
• Strong software engineering foundation with solid coding skills; Python preferred.
• Hands-on experience designing and operating cloud-native systems; GCP preferred.
• Experience with relational databases and data modeling, including schema evolution in production.
• Familiarity with event-driven architectures (Kafka, Pub/Sub, Kinesis, or similar).

Responsibilities

• Own platform components end to end: Design, build, and operate services, libraries, and schemas within the platform, from design through production, with clear ownership of their reliability and evolution.
• Design for extension and reuse: Build composable abstractions and well-defined interfaces so product teams can extend the platform without forking it or waiting on you.
• Design scalable, reliable system interactions: Contribute to the design of system interactions and data flows, making architectural decisions that balance scalability, reliability, security, and performance as the platform evolves.
• Improve reliability and operational signal: Build and evolve monitoring, alerting, dashboards, and testing pipelines that surface meaningful signal rather than noise.
• Reduce toil: Identify repeating patterns across teams and make them composable through better abstractions or new tooling, including AI-assisted tooling where it helps.
• Partner with product teams: Work as an embedded partner to feature teams, unblock delivery, and make sure platform decisions reflect what those teams actually need.

Skills

Python

Cloud-native

SQL Databases

Event-driven

RBAC/Auth

Tools

Kafka

Pub/Sub

Kinesis

OIDC/SAML

Job description

About Pivotal Health

Pivotal Health is the leading technology platform that helps healthcare providers get paid fairly in an increasingly complex reimbursement landscape. Today, many providers face persistent underpayment from health insurance companies, despite delivering high-quality care. While processes like IDR (Independent Dispute Resolution) were designed to promote fairness, they're often administrative-heavy, time-consuming, and difficult to navigate without the right tools. Pivotal Health combines software, data, and service into a seamlessly integrated, AI-driven platform that simplifies these complex reimbursement workflows. We help providers efficiently dispute underpaid claims, reduce administrative burden, and recover the reimbursement they're entitled to; without adding more work to already stretched teams. Our full-service IDR solution is just the starting point. We're building solutions that enable providers to operate with clarity, control, and confidence across the reimbursement journey.

About the Role

The product platform is the layer other product teams build on. Today that means identity and access, including customer SSO, invitations, and sessions; the organization and tenancy model; the shared services, APIs, and schemas that carry customer data between products; and the developer experience, including the tooling and agent workflows engineers use to ship. The scope grows whenever product teams need a capability that should be built once. Role-based access control, email infrastructure, the production path for the models our products depend on, and likely data ingress are next in line. When this layer is right, product teams move faster and customers have a better experience.

What You'll Do

• Own platform components end to end: Design, build, and operate services, libraries, and schemas within the platform, from design through production, with clear ownership of their reliability and evolution.
• Design for extension and reuse: Build composable abstractions and well-defined interfaces so product teams can extend the platform without forking it or waiting on you.
• Design scalable, reliable system interactions: Contribute to the design of system interactions and data flows, making architectural decisions that balance scalability, reliability, security, and performance as the platform evolves.
• Improve reliability and operational signal: Build and evolve monitoring, alerting, dashboards, and testing pipelines that surface meaningful signal rather than noise.
• Reduce toil: Identify repeating patterns across teams and make them composable through better abstractions or new tooling, including AI-assisted tooling where it helps.
• Partner with product teams: Work as an embedded partner to feature teams, unblock delivery, and make sure platform decisions reflect what those teams actually need.

Who You Are

• 5+ years of experience in fullstack, backend or platform software engineering
• Strong software engineering foundation with solid coding skills; Python preferred
• Hands-on experience designing and operating cloud-native systems; GCP preferred
• Experience with relational databases and data modeling, including schema evolution in production
• Familiarity with event-driven architectures (Kafka, Pub/Sub, Kinesis, or similar)
• Range to move between domains such as authorization, messaging infrastructure, and data pipelines without needing each to be familiar first
• Strong product instincts: you judge a system by whether it is useful and correct, and elegance comes second
• You want to know why a customer cares before you build, and you go find out: from product, from support, from the customer directly
• Self-directed and proactive: you identify problems and drive them to resolution without heavy oversight
• Comfortable in greenfield environments with evolving requirements and ambiguous ownership
• Low-ego and collaborative by default: direct, open to feedback, and more interested in shipping great work than in being right

Extra Credit Experience

• Identity and access systems (OIDC, SAML, SSO, sessions) or authorization models such as RBAC
• Transactional email or messaging infrastructure, including deliverability and bounce handling
• Data ingestion pipelines, or the tooling that moves ML models from experiment to production
• Internal libraries, SDKs, or developer tooling that other teams adopted
• Automation or AI-assisted tooling that reduced operational to